mirror of
https://github.com/meilisearch/MeiliSearch
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Delete chat.rs
This commit is contained in:
Clément Renault
parent
717a026fdd
commit
1fda05c2fd
@ -1,291 +0,0 @@
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use std::mem;
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use actix_web::web::{self, Data};
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use actix_web::{Either, HttpResponse, Responder};
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use actix_web_lab::sse::{self, Event};
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use async_openai::config::OpenAIConfig;
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use async_openai::types::{
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ChatCompletionRequestAssistantMessageArgs, ChatCompletionRequestMessage,
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ChatCompletionRequestToolMessage, ChatCompletionRequestToolMessageContent,
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ChatCompletionToolArgs, ChatCompletionToolType, CreateChatCompletionRequest, FinishReason,
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FunctionObjectArgs,
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};
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use async_openai::Client;
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use futures::StreamExt;
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use index_scheduler::IndexScheduler;
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use meilisearch_types::error::ResponseError;
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use meilisearch_types::keys::actions;
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use meilisearch_types::milli::index::IndexEmbeddingConfig;
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use meilisearch_types::milli::prompt::PromptData;
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use meilisearch_types::milli::vector::EmbeddingConfig;
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use meilisearch_types::{Document, Index};
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use serde::{Deserialize, Serialize};
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use serde_json::json;
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use crate::extractors::authentication::policies::ActionPolicy;
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use crate::extractors::authentication::GuardedData;
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use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
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use crate::routes::indexes::search::search_kind;
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use crate::search::{
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add_search_rules, perform_search, HybridQuery, RetrieveVectors, SearchQuery, SemanticRatio,
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};
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use crate::search_queue::SearchQueue;
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/// The default description of the searchInIndex tool provided to OpenAI.
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const DEFAULT_SEARCH_IN_INDEX_TOOL_DESCRIPTION: &str =
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"Search the database for relevant JSON documents using an optional query.";
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/// The default description of the searchInIndex `q` parameter tool provided to OpenAI.
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const DEFAULT_SEARCH_IN_INDEX_Q_PARAMETER_TOOL_DESCRIPTION: &str =
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"The search query string used to find relevant documents in the index. \
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This should contain keywords or phrases that best represent what the user is looking for. \
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More specific queries will yield more precise results.";
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/// The default description of the searchInIndex `index` parameter tool provided to OpenAI.
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const DEFAULT_SEARCH_IN_INDEX_INDEX_PARAMETER_TOOL_DESCRIPTION: &str =
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"The name of the index to search within. An index is a collection of documents organized for search. \
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Selecting the right index ensures the most relevant results for the user query";
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const EMBEDDER_NAME: &str = "openai";
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pub fn configure(cfg: &mut web::ServiceConfig) {
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cfg.service(web::resource("").route(web::post().to(chat)));
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}
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/// Get a chat completion
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async fn chat(
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index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
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search_queue: web::Data<SearchQueue>,
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web::Json(mut chat_completion): web::Json<CreateChatCompletionRequest>,
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) -> impl Responder {
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// To enable later on, when the feature will be experimental
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// index_scheduler.features().check_chat("Using the /chat route")?;
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if chat_completion.stream.unwrap_or(false) {
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Either::Right(streamed_chat(index_scheduler, search_queue, chat_completion).await)
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} else {
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Either::Left(non_streamed_chat(index_scheduler, search_queue, chat_completion).await)
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}
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}
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async fn non_streamed_chat(
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index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
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search_queue: web::Data<SearchQueue>,
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mut chat_completion: CreateChatCompletionRequest,
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) -> Result<HttpResponse, ResponseError> {
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let api_key = std::env::var("MEILI_OPENAI_API_KEY")
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.expect("cannot find OpenAI API Key (MEILI_OPENAI_API_KEY)");
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let config = OpenAIConfig::default().with_api_key(&api_key); // we can also change the API base
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let client = Client::with_config(config);
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assert_eq!(
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chat_completion.n.unwrap_or(1),
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1,
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"Meilisearch /chat only support one completion at a time (n = 1, n = null)"
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);
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let rtxn = index_scheduler.read_txn().unwrap();
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let search_in_index_description = index_scheduler
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.chat_prompts(&rtxn, "searchInIndex-description")
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.unwrap()
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.unwrap_or(DEFAULT_SEARCH_IN_INDEX_TOOL_DESCRIPTION)
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.to_string();
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let search_in_index_q_param_description = index_scheduler
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.chat_prompts(&rtxn, "searchInIndex-q-param-description")
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.unwrap()
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.unwrap_or(DEFAULT_SEARCH_IN_INDEX_Q_PARAMETER_TOOL_DESCRIPTION)
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.to_string();
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let search_in_index_index_description = index_scheduler
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.chat_prompts(&rtxn, "searchInIndex-index-param-description")
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.unwrap()
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.unwrap_or(DEFAULT_SEARCH_IN_INDEX_INDEX_PARAMETER_TOOL_DESCRIPTION)
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.to_string();
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drop(rtxn);
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let mut response;
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loop {
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let tools = chat_completion.tools.get_or_insert_default();
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tools.push(
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ChatCompletionToolArgs::default()
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.r#type(ChatCompletionToolType::Function)
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.function(
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FunctionObjectArgs::default()
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.name("searchInIndex")
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.description(&search_in_index_description)
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.parameters(json!({
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"type": "object",
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"properties": {
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"index_uid": {
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"type": "string",
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"enum": ["main"],
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"description": search_in_index_index_description,
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},
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"q": {
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"type": ["string", "null"],
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"description": search_in_index_q_param_description,
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}
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},
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"required": ["index_uid", "q"],
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"additionalProperties": false,
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}))
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.strict(true)
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.build()
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.unwrap(),
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)
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.build()
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.unwrap(),
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);
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response = client.chat().create(chat_completion.clone()).await.unwrap();
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let choice = &mut response.choices[0];
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match choice.finish_reason {
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Some(FinishReason::ToolCalls) => {
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let tool_calls = mem::take(&mut choice.message.tool_calls).unwrap_or_default();
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let (meili_calls, other_calls): (Vec<_>, Vec<_>) =
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tool_calls.into_iter().partition(|call| call.function.name == "searchInIndex");
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chat_completion.messages.push(
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ChatCompletionRequestAssistantMessageArgs::default()
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.tool_calls(meili_calls.clone())
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.build()
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.unwrap()
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.into(),
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);
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for call in meili_calls {
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let SearchInIndexParameters { index_uid, q } =
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serde_json::from_str(&call.function.arguments).unwrap();
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let mut query = SearchQuery {
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q,
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hybrid: Some(HybridQuery {
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semantic_ratio: SemanticRatio::default(),
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embedder: EMBEDDER_NAME.to_string(),
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}),
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limit: 20,
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..Default::default()
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};
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// Tenant token search_rules.
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if let Some(search_rules) =
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index_scheduler.filters().get_index_search_rules(&index_uid)
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{
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add_search_rules(&mut query.filter, search_rules);
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}
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// TBD
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// let mut aggregate = SearchAggregator::<SearchPOST>::from_query(&query);
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let index = index_scheduler.index(&index_uid)?;
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let search_kind = search_kind(
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&query,
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index_scheduler.get_ref(),
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index_uid.to_string(),
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&index,
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)?;
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let permit = search_queue.try_get_search_permit().await?;
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let features = index_scheduler.features();
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let index_cloned = index.clone();
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let search_result = tokio::task::spawn_blocking(move || {
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perform_search(
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index_uid.to_string(),
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&index_cloned,
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query,
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search_kind,
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RetrieveVectors::new(false),
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features,
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)
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})
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.await;
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permit.drop().await;
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let search_result = search_result?;
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if let Ok(ref search_result) = search_result {
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// aggregate.succeed(search_result);
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if search_result.degraded {
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MEILISEARCH_DEGRADED_SEARCH_REQUESTS.inc();
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}
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}
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// analytics.publish(aggregate, &req);
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let search_result = search_result?;
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let formatted = format_documents(
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&index,
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search_result.hits.into_iter().map(|doc| doc.document),
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);
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let text = formatted.join("\n");
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chat_completion.messages.push(ChatCompletionRequestMessage::Tool(
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ChatCompletionRequestToolMessage {
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tool_call_id: call.id,
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content: ChatCompletionRequestToolMessageContent::Text(text),
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},
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));
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}
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// Let the client call other tools by themselves
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if !other_calls.is_empty() {
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response.choices[0].message.tool_calls = Some(other_calls);
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break;
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}
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}
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_ => break,
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}
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}
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Ok(HttpResponse::Ok().json(response))
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}
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async fn streamed_chat(
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index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
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search_queue: web::Data<SearchQueue>,
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mut chat_completion: CreateChatCompletionRequest,
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) -> impl Responder {
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assert!(chat_completion.stream.unwrap_or(false));
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let api_key = std::env::var("MEILI_OPENAI_API_KEY")
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.expect("cannot find OpenAI API Key (MEILI_OPENAI_API_KEY)");
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let config = OpenAIConfig::default().with_api_key(&api_key); // we can also change the API base
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let client = Client::with_config(config);
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let response = client.chat().create_stream(chat_completion).await.unwrap();
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actix_web_lab::sse::Sse::from_stream(response.map(|response| {
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response
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.map(|mut r| Event::Data(sse::Data::new_json(r.choices.pop().unwrap().delta).unwrap()))
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}))
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}
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#[derive(Deserialize)]
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struct SearchInIndexParameters {
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/// The index uid to search in.
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index_uid: String,
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/// The query parameter to use.
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q: Option<String>,
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}
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fn format_documents(index: &Index, documents: impl Iterator<Item = Document>) -> Vec<String> {
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let rtxn = index.read_txn().unwrap();
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let IndexEmbeddingConfig { name: _, config, user_provided: _ } = index
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.embedding_configs(&rtxn)
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.unwrap()
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.into_iter()
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.find(|conf| conf.name == EMBEDDER_NAME)
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.unwrap();
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let EmbeddingConfig {
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embedder_options: _,
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prompt: PromptData { template, max_bytes },
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quantized: _,
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} = config;
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#[derive(Serialize)]
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struct Doc<T: Serialize> {
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doc: T,
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}
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let template = liquid::ParserBuilder::with_stdlib().build().unwrap().parse(&template).unwrap();
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documents
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.map(|doc| {
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let object = liquid::to_object(&Doc { doc }).unwrap();
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template.render(&object).unwrap()
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})
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.collect()
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}
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